Adaptive Occupied-Area Collision Prioritization in Road Traffic
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Solution Overview
Problem
Existing solutions for avoiding collisions between moving vehicles and other road users in complex traffic situations are inefficient due to the inability to quickly and effectively filter out relevant data from overwhelming sensor inputs, leading to delayed reaction times and increased resource usage.
Innovation Solution
A method that divides the vehicle's environment into distinct areas, classifies and prioritizes road users based on their groups and location, determining collision probabilities to focus processing on high-priority road users, thereby filtering out relevant data quickly and allowing for timely intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensors provide comprehensive data about all road users in the vehicle environment, then detection completeness is improved, but data processing time and resource usage increase
Solution Approach 1:
The vehicle environment is divided into multiple location areas (first location area, second location area, etc.) with different occupied area characteristics. Road users in different locations are processed with different priorities, allowing the system to focus computational resources on high-risk areas while maintaining comprehensive detection coverage.
Solution Approach 2:
Different location areas are assigned different priority levels based on their occupied area characteristics. The system applies different processing strategies to different spatial regions, intensifying analysis in high-priority areas where collision risk is higher and reducing analysis depth in low-priority areas.
2Measurement precision
If the system processes collision probability for all detected road users equally, then detection accuracy is improved, but computational resource usage increases
Solution Approach 1:
Road users are segmented into different priority groups based on their location in the vehicle environment. The system calculates collision probability with high precision for high-priority road users in critical location areas, while using reduced precision or skipping calculation for low-priority road users, thereby optimizing computational resource allocation.
Solution Approach 2:
The system applies different levels of measurement precision to different road users based on their spatial location and priority classification. High-priority road users receive full precision collision probability calculation, while low-priority road users receive simplified assessment, matching computational effort to actual risk levels.
3Device complexity
If the vehicle maintains current driving behavior without adaptive response, then system simplicity is improved, but collision avoidance effectiveness decreases
Solution Approach 1:
The system dynamically adapts driving behavior based on real-time collision probability assessments. When high-priority road users are detected with high collision probability in critical location areas, the system automatically adjusts vehicle parameters (acceleration, braking, steering) to avoid collisions, creating a dynamic response system that balances simplicity with effectiveness.
Solution Approach 2:
The system implements a feedback loop where sensor data about road users and their locations continuously informs collision probability calculations, which in turn trigger appropriate driving behavior adjustments. This closed-loop control ensures collision avoidance effectiveness while maintaining relatively simple system architecture through rule-based decision making.
Data Source
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AI summary
The present invention relates to a method for avoiding collisions of a moving vehicle with other road users in the surroundings of the vehicle, comprising at least the method steps of: a) detecting, by means of one or more sensors, the vehicle surroundings and the other road users located therein; b) dividing the vehicle surroundings into a plurality of occupied areas; c) classifying the other road users detected in method step a), wherein, by means of the classification, at least one road user group is assigned to each of the other road users; d) prioritising the road user classified in method step c), taking into account both the classification carried out in method step c) and the occupied area defined in method step b), wherein road users from one or more predetermined road user groups in the particular occupied area are given a high priority and road users from other, non-predetermined road user groups in the particular occupied area are given a lower priority; and e) determining the probability of collision of the other road users with the vehicle, wherein the collision probability is determined in accordance with the prioritisation carried out in method step d) and the collision probability of the other road users having a high priority is determined first; f) changing or maintaining the current driving behaviour of the vehicle on the basis of the collision probabilities determined in method step e).